A STUDY ON THE APPLICATION OF ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON UNDERGRADUATE ACADEMIC PERFORMANCE

CHAPTER ONE INTRODUCTION 1.1 Background of the Study Artificial intelligence (AI) has increasingly become a vital part of various industries, revolutionizing traditional approaches and offering sophisticated solutions to complex problems. In the education sector, AI technologies are progressively being integrated to enhance teaching and learning processes. These technologies include intelligent tutoring systems, automated grading software, adaptive learning platforms, and virtual teaching assistants—all designed to improve learning outcomes and offer personalized educational experiences (Chen et al., 2020). The introduction of AI in education dates back to the 1960s, beginning with early computer-assisted instruction. However, significant advancements have occurred in the past two decades due to improvements in algorithms and computing power. Early AI educational tools such as the PLATO system laid the groundwork for more advanced innovations like IBM’s Watson Tutor and AI-powered platforms such as Coursera and Khan Academy (Luckin et al., 2016). The application of AI in higher education is diverse and continually evolving. Intelligent tutoring systems like Carnegie Learning's MATHia and Pearson's MyLab offer personalized feedback and adaptive learning paths tailored to each student’s performance (Pane et al., 2015). Automated grading platforms, for instance Gradescope, streamline the assessment process by providing consistent and unbiased grading, enabling educators to focus more on teaching (Jordan, 2019). Moreover, AI-powered tools like chatbots and virtual teaching assistants enhance student engagement and support. For example, Georgia State University employed an AI chatbot named Pounce to assist students with administrative queries and tasks, which contributed to increased student retention rates (Bailey et al., 2018). Research indicates that AI technologies have the potential to boost academic success by delivering customized learning experiences that cater to individual learning styles and needs. Personalized learning platforms that adapt content based on student interactions have been shown to improve understanding and retention (Chen et al., 2020). Additionally, advanced tutoring systems offer instant feedback and guidance, helping students address their weak points more effectively (VanLehn, 2017). Nonetheless, the impact of AI on academic performance is not uniformly positive. Studies suggest that AI effectiveness depends on various factors, including the quality of the system, the subject matter, and the learning environment (Luckin et al., 2016). Concerns also exist about over-reliance on AI potentially diminishing students’ critical thinking and problem-solving skills (Holstein et al., 2019). Despite its advantages, AI use in education raises several challenges and ethical issues. A major concern is the digital divide, where students from less privileged backgrounds may lack access to AI technologies, thereby exacerbating existing educational inequalities (Jones, 2021). The extensive data collection involved in AI-driven personalized learning also triggers worries about student privacy and data security (Pardo & Siemens, 2014). Furthermore, the ethical debate continues over replacing human teachers with AI, which risks undervaluing the human elements such as empathy, creativity, and critical insight that educators bring to the classroom (Holstein et al., 2019). While AI can offer valuable support, it cannot fully replicate these uniquely human qualities. The promise of AI in education is substantial but requires careful assessment of its implementation and effects. Ongoing research and development are necessary to enhance AI tools’ efficiency and accessibility. Collaboration between policymakers and educational institutions is vital to bridge the digital divide and ensure equitable AI access for all students (Jones, 2021). Training educators to effectively integrate AI into teaching practices is also essential to harness AI’s benefits while preserving the core human aspects of education. Moreover, cooperation among AI developers, educators, and researchers will be crucial to creating AI systems that are ethical, effective, and fair. Accordingly, this study aims to evaluate the use of artificial intelligence and its impact on the academic performance of undergraduate students, focusing on Gregory University students in Imo State. 1.2 Statement of the Problem The rapid advancement of artificial intelligence technology has profoundly affected many sectors, including education. With AI increasingly incorporated into educational methods, it is important to understand how these technologies influence students’ academic success. This study intends to investigate the effects of AI on the academic performance of undergraduates. AI applications such as intelligent tutoring systems, personalized learning platforms, and automated grading tools have the potential to enhance learning through customized feedback and support (Chen et al., 2020). However, empirical evidence is necessary to verify these claims and measure the extent of AI’s benefits on educational outcomes (Smith & Anderson, 2019). Additionally, concerns about equitable access to AI technology must be addressed, as students from disadvantaged backgrounds may have limited use of these tools due to unequal availability and differences in digital literacy (Jones, 2021). Therefore, this study not only examines the overall effect of AI on academic performance but also explores how these effects differ among various student groups. Hence, the research focuses on assessing the use of artificial intelligence and its impact on the academic achievements of undergraduates at Gregory University, Imo State. 1.3 Objectives of the Study Generally, this study assesses the use of artificial intelligence and its effects on the academic performance of undergraduate students . The specific objectives are: i. To evaluate the impact of AI on the academic performance of undergraduate students at Gregory University. ii. To examine the effectiveness of AI personalized learning platforms in improving students’ understanding and retention of course materials. iii. To analyze the efficiency of AI in providing academic support to undergraduate students at Gregory University. 1.4 Research Questions The study aims to answer the following questions: i. What is the impact of AI on the academic performance of undergraduate students at Gregory University? ii. How effective are AI personalized learning platforms in enhancing students’ comprehension and retention of course content? iii. How efficient is AI in providing academic support to undergraduate students at Gregory University? 1.5 Significance of the Study The findings of this study are important because AI technologies have the potential to enhance educators’ capabilities by automating routine tasks such as grading and offering real-time insights into student progress. This research will explore how AI can be leveraged to free educators’ time, allowing them to dedicate more effort to impactful teaching activities and targeted student support. Moreover, the study’s outcomes will contribute to academia by identifying key factors influencing the successful integration of AI in educational environments. These insights will inform the future development and implementation of AI tools, helping developers design more effective and user-friendly applications tailored to the needs of both students and educators. 1.6 Scope of the Study This research focuses on the use of artificial intelligence and its effects on the academic performance of undergraduate students. Empirically, the study will assess AI’s impact on students’ academic performance, evaluate the effectiveness of AI personalized learning platforms in enhancing understanding and retention, and analyze AI’s efficiency in academic support within Gregory University. Geographically, the study is confined to Gregory University in Imo State. 1.7 Limitations of the Study As with any research, this study faced certain limitations: Time: The researcher experienced time constraints, having to balance the study with other academic responsibilities such as attending lectures and other required educational activities. Finance: Conducting this study involved financial costs related to tasks such as typesetting, printing, sourcing relevant materials and literature, and data collection. Availability of Materials: The researcher encountered difficulties in obtaining sufficient literature on the topic, due to the limited amount of existing research in this area, which posed a challenge to the study. 1.8 Definition of Terms Artificial Intelligence (AI): A field within computer science focused on creating systems capable of performing tasks that normally require human intelligence, including learning, reasoning, problem-solving, perception, and understanding language.